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Inferring spatially transient gene expression pattern from spatial transcriptomic studies

Jan Kueckelhaus, Jasmin von Ehr, Vidhya M. Ravi, Paulina Will, Kevin Joseph, Juergen Beck, Ulrich G. Hofmann, Daniel Delev, Oliver Schnell, View ORCID ProfileDieter Henrik Heiland
doi: https://doi.org/10.1101/2020.10.20.346544
Jan Kueckelhaus
1Microenvironment and Immunology Research Laboratory, Medical Center, University of Freiburg, Germany
2Department of Neurosurgery, Medical Center, University of Freiburg, Germany
3Faculty of Medicine, Freiburg University, Germany
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Jasmin von Ehr
1Microenvironment and Immunology Research Laboratory, Medical Center, University of Freiburg, Germany
2Department of Neurosurgery, Medical Center, University of Freiburg, Germany
3Faculty of Medicine, Freiburg University, Germany
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Vidhya M. Ravi
1Microenvironment and Immunology Research Laboratory, Medical Center, University of Freiburg, Germany
2Department of Neurosurgery, Medical Center, University of Freiburg, Germany
3Faculty of Medicine, Freiburg University, Germany
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Paulina Will
1Microenvironment and Immunology Research Laboratory, Medical Center, University of Freiburg, Germany
2Department of Neurosurgery, Medical Center, University of Freiburg, Germany
3Faculty of Medicine, Freiburg University, Germany
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Kevin Joseph
1Microenvironment and Immunology Research Laboratory, Medical Center, University of Freiburg, Germany
2Department of Neurosurgery, Medical Center, University of Freiburg, Germany
3Faculty of Medicine, Freiburg University, Germany
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Juergen Beck
2Department of Neurosurgery, Medical Center, University of Freiburg, Germany
3Faculty of Medicine, Freiburg University, Germany
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Ulrich G. Hofmann
3Faculty of Medicine, Freiburg University, Germany
4Neuroelectronic Systems, Medical Center, University of Freiburg, Germany
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Daniel Delev
5Department of Neurosurgery, RWTH University of Aachen, Aachen, Germany
6Neurosurgical Artificial Intelligence Laboratory Aachen (NAILA), Department of Neurosurgery, RWTH University of Aachen, Aachen, Germany
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Oliver Schnell
2Department of Neurosurgery, Medical Center, University of Freiburg, Germany
3Faculty of Medicine, Freiburg University, Germany
7Translational NeuroOncology Research Group, Medical Center, University of Freiburg, Germany
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Dieter Henrik Heiland
1Microenvironment and Immunology Research Laboratory, Medical Center, University of Freiburg, Germany
2Department of Neurosurgery, Medical Center, University of Freiburg, Germany
3Faculty of Medicine, Freiburg University, Germany
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  • ORCID record for Dieter Henrik Heiland
  • For correspondence: dieter.henrik.heiland@uniklinik-freiburg.de
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Abstract

Spatial transcriptomic is a technology to provide deep transcriptomic profiling by preserving the spatial organization. Here, we present a framework for SPAtial Transcriptomic Analysis (SPATA, https://themilolab.github.io/SPATA), to provide a comprehensive characterization of spatially resolved gene expression, regional adaptation of transcriptional programs and transient dynamics along spatial trajectories.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • DISCLOSURE OF CONFLICTS OF INTEREST: No potential conflicts of interest were disclosed by the authors.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted October 21, 2020.
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Inferring spatially transient gene expression pattern from spatial transcriptomic studies
Jan Kueckelhaus, Jasmin von Ehr, Vidhya M. Ravi, Paulina Will, Kevin Joseph, Juergen Beck, Ulrich G. Hofmann, Daniel Delev, Oliver Schnell, Dieter Henrik Heiland
bioRxiv 2020.10.20.346544; doi: https://doi.org/10.1101/2020.10.20.346544
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Inferring spatially transient gene expression pattern from spatial transcriptomic studies
Jan Kueckelhaus, Jasmin von Ehr, Vidhya M. Ravi, Paulina Will, Kevin Joseph, Juergen Beck, Ulrich G. Hofmann, Daniel Delev, Oliver Schnell, Dieter Henrik Heiland
bioRxiv 2020.10.20.346544; doi: https://doi.org/10.1101/2020.10.20.346544

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